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AI Web Programming (Streamlit)

Make AI data analysis and modeling results into a Web Program.

(5.0) 1 reviews

62 learners

  • bestdjango
시각화
데이터분석
웹개발
streamlit
Machine Learning(ML)
Django
Seaborn
jupyter-notebook

What you will learn!

  • Start AI machine learning development.

  • Start developing web programs.

  • And connect them.

  • Streamlit Usage, Working Principle, Pros and Cons

Get started with AI Web Programming.

AI machine learning/deep learning results can be opened as a web program.

  • With Streamlit, you can create web programs very easily.

  • You will learn not only how to use Streamlit, but also its core principles.

  • If you have Django experience, Streamlit features will be an upgrade.

  • You can also create a ChatGPT program easily.

Learn about these things

(1) Basic explanations for beginners

We offer both intermediate and beginner courses, and even provide basic usage lessons to help beginners get started (machine learning, Jupyter Notebooks, Streamlet, Django, etc.).

(2) Web programming for data analysts

From a data analyst's perspective, I am studying web programming, which is considered difficult, step by step.

  • Data analysis is done using web programs.

  • Machine learning predictions are made through web programs.

  • Create a data dashboard as a web program.


(3) It's more than just simple usage.

The official documentation is sufficient for simple usage of the Streamlit package. It explains the underlying principles, caveats, and its pros and cons compared to common web programming methods like Django.

Know in advance

(1) What is AI Web Programming?

This term is not an official term, it is a term I made up for convenience.

As the number of tasks to open AI machine learning/deep learning results as web programs is increasing, this type of programming is called AI Web Programming.

You may misunderstand that this is web programming with ChatGPT, but that is not the case.

(2) Is the official documentation sufficient for how to use Streamlit?

That's right. The official documentation is well-written, so you can learn basic usage on your own from the official documentation.

This course goes beyond basic usage to explain the internal workings and precautions, and compares the pros and cons with general web programming methods.

(3) Beginners should study the basics first.

If you find the lecture difficult after listening to it from the beginning, study the (basic) section below first.

I tried to convey it in an easy and step-by-step manner.

Things to note before taking the course

Practice environment

  • Operating System and Version (OS): The course is taught on Windows, but both MacOS and Linux are also available.

  • I will be teaching using PyCharm (v2023 free version), but please use an editor you are familiar with (such as VSCode).


  • Streamlit (v1.30), Jupyter-Notebook (v7.0), Django (v5.0)

  • Although the lecture is based on the above version, it uses the basic API, so the version has little effect.

Learning Materials

  • Source code and lecture reference materials provided

  • During the lecture, we explain not only coding but also concepts related to coding.

Player Knowledge and Precautions

  • Basic knowledge of Python is required, and experience with Django is a plus.

  • To save study time, I edited the video by reducing idle time.


Recommended for
these people

Who is this course right for?

  • Developer starting Machine Learning

  • Developer starting web programming

  • A person aiming to express Data Science results via web program.

Need to know before starting?

  • With just Python basics, you can start the basic course.

  • Data analysis or web programming experience preferred.

Hello
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Answers

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Rating

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Curriculum

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80 lectures ∙ (9hr 56min)

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    princekey

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